Automatic Target Recognition using Invariant Target Features and Statistical Classifier

Nitin, V Kamath and Sudesh, K Kashyap and Shantha Kumar, N Automatic Target Recognition using Invariant Target Features and Statistical Classifier. In: International conference on innovative science and engineering technology, 8-9 April 2011, VVP Engineering College, Rajkot, Gujarat, India.

Full text available as:
[img] PDF - Accepted Version
Restricted to Registered users only

Download (348Kb) | Request a copy

    Abstract

    Automatic Target Recognition refers to the autonomous or aided target detection and identification by processing of information extracted from the various sensors. In this paper a novel concept is proposed to detect multiple targets and perform pre-classification to categorize the targets based on their aspect ratio. Features are computed using Zernike moments to yield target feature set which are invariant to shift, size and orientation. A novel approach for classification of the target features by Weighted Minimum Mean Distance is also introduced to reduce the false classifications. The proposed approach has been successfully verified on various target images

    Item Type: Conference or Workshop Item (Paper)
    Uncontrolled Keywords: Automatic Target Recognition, Canny Edge Detection, Zernike moments, Weighted Minimum Mean Distance, Target Aspect Ratio
    Subjects: ENGINEERING > Engineering (General)
    Division/Department: Other, Flight Mechanics and Control Division, Flight Mechanics and Control Division
    Depositing User: Dr Sudesh Kumar Kashyap
    Date Deposited: 30 May 2011 15:32
    Last Modified: 08 Jun 2011 13:55
    URI: http://nal-ir.nal.res.in/id/eprint/9180

    Actions (login required)

    View Item